A. Younesi (0000-0003-1919-926X)

Biography

Abdollah Younesi received his B.Sc., M.Sc., ‎and Ph.D. ‎degrees in Electrical Engineering ‎from the Faculty of ‎Technical Engineering, ‎Mohaghegh Ardabili University, ‎Ardabil, Iran in ‎‎2012, 2015, and 2021 respectively. He was ‎‎a Senior Research Associate ‎in the ‎School of Computing Science, ‎University of East ‎Anglia, Norwich, UK in 2022. He is a Ph.D. researcher in the Department of Electrical Engineering, University of Connecticut, Connecticut, USA. Throughout his ‎academic ‎career, he has been selected ‎as a Talent Student ‎of the University several times in ‎B.Sc., M.Sc., ‎and Ph.D. In addition, he was chosen as the top ‎‎talent of the National Elite Foundation of Iran ‎twice in ‎‎2018 and 2019. ‎His areas of ‎interest are power system decarbonization, power system non-linear optimization and simulation, application of reinforcement learning (RL) to power system control, time series analysis and forecasting, resilient operation of power systems, smart grid technology, renewable & storage energy, dispatch control hierarchy, data analytics, engineering management, active distribution systems, microgrid, digital image processing.

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University of Connecticut: Storrs, CT, US

2022-12-07 to 2023-03-01 | PhD Researcher (Electrical Engineering)

Employment

https://orcid.org/0000-0003-1919-926X

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Biography

Activities

Employment (2)

University of Connecticut: Storrs, CT, US

University of East Anglia: Norwich, Norfolk, GB

Education and qualifications (4)

University of Connecticut: Storrs, CT, US

University of Mohaghegh Ardabili: Ardabil, Ardabil, IR

University of Mohaghegh Ardabili: Ardabil, Ardabil, IR

University of Mohaghegh Ardabili: Ardabil, Ardabil, IR

Works (18)

Energy hubs components and operation: State-of-the-art review

Enhancing the resilience of zero-carbon energy communities: Leveraging network reconfiguration and effective load carrying capability quantification

AC Optimal Power Flow in Power Systems With Renewable Energy Integration: A Review of Formulations and Case Studies

Developing an Integration of Smart-Inverter-Based Hosting-Capacity Enhancement in Dynamic Expansion Planning of PV-Penetrated LV Distribution Networks

Trends in modern power systems resilience: State-of-the-art review

Enhancing the Resilience of Operational Microgrids Through a Two-Stage Scheduling Strategy Considering the Impact of Uncertainties

A Quantitative Resilience Measure Framework for Power Systems Against Wide-Area Extreme Events

Assessing the Use of Reinforcement Learning for Integrated Voltage/Frequency Control in AC Microgrids

Modeling of thermodynamic properties of carrot product using ALO, GWO, and WOA algorithms under multi-stage semi-industrial continuous belt dryer

Q-learning Based Supervisory PID Controller for Damping Frequency Oscillations in a Hybrid Mini/Micro-Grid

Application of reinforcement learning for generating optimal control signal to the IPFC for damping of low-frequency oscillations

A Robust Discrete FuzzyP+FuzzyI+FuzzyD Load Frequency Controller for Multi-Source Power System in Restructuring Environment

An online Q-learning based multi-agent LFC for a multi-area multi-source power system including distributed energy resources

Reinforcement learning based PID controller design for LFC in a microgrid

Robust Adaptive Load Frequency Controller Based on Reinforcement Learning in an Inter-Connected Power System

An Online Q-learning Based Multi-Agent LFC for a Multi-Area Multi-Source Power System Including Distributed Energy Resources

Design of PSS3B stabilizer using KH Algorithm and Q-Learning for damping Low-frequency Oscillations in SMIB

Optimal design of a robust discrete parallel FP + FI + FD controller for the Automatic Voltage Regulator system